Phenotyping Food Entrainment: Motion Sensors and Telemetry Are Equivalent
Bibliographic record
Abstract
Rats can anticipate a daily meal by entrainment of a circadian timekeeping mechanism that is anatomically separate from the light-entrainable circadian pacemaker located in the suprachiasmatic nucleus. The dorsomedial nucleus of the hypothalamus (DMH) has been claimed to be critical for the expression of circadian rhythms of food anticipatory activity, but efforts to confirm this finding have so far failed. Failure to confirm that DMH ablation disrupts or eliminates food anticipatory rhythms has been attributed to the use of overhead motion sensors rather than telemetry to measure locomotor activity. To examine the relationship between motion sensor and telemetric measures of locomotor activity, transponders were implanted into the peritoneal cavity of adult male rats, and activity was recorded continuously by both telemetry and infrared motion sensors. Activity counts were approximately 4 fold higher as detected by telemetry, but normalized activity patterns were virtually identical for the two measures during ad-lib food access, 4 h/day food restriction and total food deprivation after food restriction. Overhead motion sensors and telemetry are equivalent measures of food anticipatory activity in rats. Telemetry is an effective tool for continuous recording of body temperature but has no advantages over infrared motion sensors for measuring food anticipatory activity rhythms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".